Method for controlling a hybrid vehicle

ABSTRACT

In a vehicle equipped with an engine and a regenerative system, the quantity of energy storage by the regenerative system is scheduled, and fuel efficiency and driving ease are controlled. If the destination of a vehicle and a route to reach it are not indicated, automatic scheduling is performed. Vehicle scheduling is performed by predicting the distribution of height positions the vehicle is predicted to reach at future points of time and using the representative value of the height at each point of time.

BACKGROUND OF THE INVENTION

The present invention relates to a method for controlling a hybridvehicle, and more particularly to a method for optimally controlling ahybrid vehicle having an engine and a regenerative system whichconverts, stores and discharges the kinetic energy of the vehicle.

In braking with a drum brake or a disk brake, the kinetic energy of thevehicle is discarded as heat. On the other hand, there are some vehicleswhich improve fuel efficiency with a regenerative system for making useof their kinetic energy when storing. For instance, a vehicle disclosedin the Japanese Published Unexamined Patent Application No. Hei 10-98805is equipped with a system which converts kinetic energy into electricenergy with a rotary machine and stores the converted energy in itsbattery. Other known examples include a regenerative system usingelastic elements, compressed air, a flywheel, a hydraulic pump and soforth, described in the Basics and Theory, Automotive TechnologyHandbook, Vol. 1, issued by the Automotive Technology-Society (ofJapan), Dec. 1, 1990, pp. 137-140.

A hybrid vehicle equipped with one or another of these regenerativesystems can enhance fuel efficiency and driving ease by controlling theoutput ratio between a primary power source, such as an engine, and asecondary power source consisting of a regenerative system. Forinstance, a method by which the destination is entered to determine thetraveling route and a schedule for the state of charge of the battery onthe route, as disclosed in the Japanese Published Patent Application No.Hei 8-126116, can be applied to a vehicle provided with a rotary machine(motor) and a storage battery. According to this method, the state ofcharge of the battery is increased before an upward slope to helpprevent deterioration of the driving conditions due to a power shortageon the climb. Further, by reducing the state of charge of the batteryand increasing the quantity of energy regenerated by a regenerativebrake, improve fuel efficiency and enhanced driving ease are provided,while ensuring a sufficient level of braking force.

There is a problem in that no long term scheduling can be done unlessthe destination and the route thereto are indicated. Furthermore, eventhough the destination and the route thereto are specified and thedriving plan is made, if the vehicle deviates from the planned route asa result of an error in driving or a change in the driver's plans, bothfuel efficiency and driving ease will deteriorate.

SUMMARY OF THE INVENTION

According to the present invention, a hybrid vehicle is controlled bycalculating the distribution of heights the vehicle is predicted toreach for each point of time; calculating the representative value ofheight at each point of time from this distribution of heights for eachpoint of time; and, it being assumed that the vehicle will pass thepoint of representative height of that representative value, schedulingthe energy recovery and discharge quantities of the regenerative systemand the engine output. The method according to the invention makes itpossible to make a medium to long range driving plan even where thedestination and the route thereto are not specified, and thereby toimprove fuel efficiency.

According to the invention, a hybrid vehicle is controlled bycalculating the distribution of probabilities pertaining to the energystate of a vehicle at each point of time from the current moment onward,determining the setting range of target energy storage quantity at eachpoint of time according to the dispersion of the distribution of theenergy state, and scheduling the energy regeneration and dischargequantities of the regenerative system and the engine output so as to beconsistent with the limit range. As a result, when a driving plan ismade according to the scheduling method described above, the drivingconditions can be enhanced by providing an excess or a shortage ofregenerative system energy.

In the method of above, preferably either the distribution of heights ora distribution pertaining to the vehicle speed or both are used as thedistribution(s) of probabilities pertaining to the vehicle energy stateto control the hybrid vehicle. As a result, a driving plan can be madeon the basis of determinants of the state of energy to achievesatisfactory control.

In the method above, a hybrid vehicle is controlled by calculating thereachable point at each point of time and the probability of arrivingthere from the ratio of branching into different routes at each junctionahead of the vehicle and the predicted time to cover a given section,determining the height of the point to be reached, calculating thedistribution of the probabilities of the vehicle's arrival at a givenheight at that point of time, and calculating the distribution ofprobabilities pertaining to the energy state of the vehicle at eachpoint of time on the basis of the distribution of height probabilitiesso calculated.

A hybrid vehicle is controlled by calculating the distribution ofheights of points contained in a set consisting of at least either thepoints within a prescribed spatial range from the current position ofthe vehicle or the points reachable within a prescribed length of time,and setting the target quantity of energy storage of the regenerativesystem so that it become closer to the center of the proper range as thedispersion of the height distribution increases. As a result, thevehicle can be controlled in a relatively small number of proceduralsteps though inferior in accuracy.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of the configuration of a vehicle.

FIG. 2 is a configuration of a vehicle controller for a vehicle.

FIG. 3 is a block diagram of a processing system of a preferredembodiment of the invention.

FIG. 4 is a flowchart of the processing steps in a preferred embodimentof the invention.

FIG. 5 is a diagram illustrating a height distribution for an embodimentof the invention.

FIG. 6 is a diagram illustrating the output characteristics of a batteryin an embodiment of the invention.

FIG. 7 is a diagram illustrating the charge/discharge efficiencycharacteristics of the battery in an embodiment of the invention.

FIG. 8 is a diagram for determination of the driving output for a targetaxle in an embodiment of the invention.

FIG. 9 is another diagram pertaining to the determination of the drivingoutput for the target axle.

FIG. 10A illustrates a sample road environment.

FIG. 10B illustrates variations in the state of charge of the vehicle'sbattery under control without prediction.

FIG. 10C illustrates variations in the state of charge of the vehicle'sbattery where the vehicle is controlled according to the invention.

FIG. 11 is a block diagram block diagram for processing in anotherembodiment of the invention.

DESCRIPTION OF THE SPECIFIC EMBODIMENTS

A vehicle control method according to one embodiment of the presentinvention is described below with reference to accompanying drawings.With reference to FIG. 1, the configuration of a vehicle control systemis depicted for a vehicle control method according to this embodiment.

The vehicle system according to a first embodiment is equipped with, asits power sources, an engine 101 which is an internal combustion engine,as well as a rotary machine system consisting of a generator 103 and amotor 105. These items are connected to power transmission shafting 100consisting of gears and a clutch, and together drive wheels 109, eitherdirectly or indirectly. The surplus of electric power generated by thegenerator 103 which is not consumed by the motor 105 is stored inbattery 107, and discharged as the power supply is required. A systemwhich converts, stores and supplies the kinetic energy or the engineoutput of a vehicle is called a regenerative system. In this embodiment,the generator 103, the motor 105 and the battery 107 constitute aregenerative system.

Engine 101 is controlled and monitored by an engine controller 117. Thegenerator 103 is controlled and monitored by a generator controller 119.Motor 105 is controlled and monitored by a motor controller 123. Thebattery 107 is controlled and monitored by a battery controller 121.These controllers in turn, are controlled by a vehicle controller 115.An internal network 125 connects the controllers to one another.

The vehicle system, fitted with a current position detector 131consisting of a GPS (global positioning system) antenna and other items,supplies information on the vehicle's current position to the vehiclecontroller 115. A map database 133, at the request of the vehiclecontroller 115, supplies the vehicle controller 115 with data on thecurrent position of the vehicle and the widths, intersections andheights of nearby and other local roads. A road information receiver135, comprising a road beacon receiver, a radio antenna and the like,receives publicly available information on road traffic, and supplies itto the vehicle controller 115.

An accelerator pedal 127 is fitted with a position meter (not shown),which supplies information on the accelerator pedal treading angle tothe vehicle controller. A brake pedal 129 is fitted with a positionmeter (not shown), which supplies information on the brake pedaltreading angle to the vehicle controller. A brake 111, connected to thebrake pedal 129 either mechanically or electrically, applies brakingpower to the driving wheels according to the treading angle of the brakepedal. This brake converts the kinetic energy of the driving wheels witheither brake pads or brake drums into heat, which is discarded into theatmosphere.

Details of the vehicle controller 115 are described with reference toFIG. 2. The vehicle controller consists of a CPU 201, a ROM 203, a RAM205, a sensor 10, and a network IO connected to one another by a bus210. The CPU 201 controls the vehicle in accordance with a controlprogram stored in the ROM 203. Necessary variables for computation bythe CPU 201 are stored into the RAM 205 as data. Data transmission andreception to and from the current position detector 131, map database133, and road information receiver 135 and reception of signals on theaccelerator pedal treading angle and brake pedal treading angle areaccomplished via a sensor IO 207, and the results are stored in the CPU201 or the RAM 205. Data transmission and reception to and from theinternal network 125 are accomplished via the network 10 209, and theresults are stored in the CPU 201 or the RAM 205. The engine controller117, generator controller 119, battery controller 121, and motorcontroller 123 have similar configurations to that of the vehiclecontroller 115 shown in FIG. 2.

FIG. 3 is a block diagram of the vehicle control method according tothis embodiment. The process shown in this block diagram is executed bythe vehicle controller 115. This embodiment does not use a target routesetting operation 1101.

An arrival range prediction block 301, on the basis of the currentposition detected by the current position detector 131, geographicaldata from the map database 133 and traffic jam information from the roadinformation receiver 135, calculates a reachable range S(t) from thecurrent position. This calculation is performed for each point of time tfrom the current time until a prescribed point of time, for instance atfive-minute intervals until 30 minutes later. Calculation of S(t) isaccomplished by determining the required length of time to cover thedistance between adjacent ones of link points stored in the mapdatabase. It is assumed that the distance between each pair of adjacentlink points is traveled at the maximum speed the level of roadcongestion allows. The system identifies a reachable link point bycomprehensively searching all road connections between each pair ofadjacent link points. The link points are all the junctions, branchingpoints and points positioned at prescribed intervals on roads betweenjunctions.

An arrival probability calculation part 303 calculates the probabilityof the arrival of the vehicle at a point of time t at each link pointincluded in S(t). In the probability calculation, the probability ofroute choice is set for each branching point in the following manner.Probabilities are so set that the greater the width of a given road inthe map database 133, the more likely the road is chosen, while the moreintense its congestion according to the road information receiver 135,the less likely the road is chosen. It is supposed that the greater theroad width, the faster the vehicle will travel that the more intense thetraffic jam, the slower the vehicle will travel. The distribution oftime periods taken to cover the distance between each pair of adjacentlink points is calculated on that basis. The probability Pos(s;t) of thevehicle's presence at each link point s included in S(t) after a pointof time t is calculated from the probability of route choice at eachbranching point and the distribution of traveling time lengths betweenlink points. If the vehicle is not right on any given link point, it isassumed to be on the nearest link point.

An elevation or height distribution calculation block 305 calculates thedistribution of heights where the vehicle will be positioned from thereachable range S(t) and the arrival probability Pos(s;t) at each pointof time t and height data from the map database. Thus the followingdistribution is calculated. The height of a link point read from the mapdatabase being represented by H(s), the relative height from the lowestlevel of the road (e.g. −200 m) from its highest level (e.g. 4000 m) isdivided into sections HH(i) of a prescribed length (e.g. 1 m). For eachs included in S(t), HH(t;i) determined by the following equation iscalculated out for each section HH(i), S(t;i) representing all whoseH(s) belongs to the section HH(i). $\begin{matrix}{{{hh}\left( {t;i} \right)} = {\sum\limits_{s \in {S{({t;i})}}}{{Pos}\left( {s;t} \right)}}} & (1)\end{matrix}$

In this way, the probability of the presence of the vehicle at a pointof time t in each height-based section is calculated.

FIG. 5 is a graph in which the height-based section is plotted on thehorizontal axis, and the probability of presence, on the vertical axis.The relationship shown in this graph is the distribution ofprobabilities of heights at which the vehicle is present at a point oftime t. While a finite number of link points is used here, thedistribution of heights in a continuous sequence may as well becalculated by assuming S(t) to be a continuum and the length of theheight-based section is shifted to an infinitesimal.

A representative height value setting part 307 calculates therepresentative value ho(t) of height at each point of time from theprobability of height h(t) at each point of time t. The average heightgiven by the following equation is used as the representative value:$\begin{matrix}{{{ho}(t)} = {{E\left( {h\left( {i;t} \right)} \right)} = {\sum\limits_{i}{{H^{\prime}(i)} \times {{hh}\left( {t;i} \right)}}}}} & (2)\end{matrix}$

where H′(i) is the average height in the section HH(i).

An alternative way to calculate the average is to calculate therepresentative value at a point of time t with the unevenness of theshape of the probability distribution h(t) taken in account. Forinstance, where h(t) expands in the increasing direction of t,satisfactory control can be achieved in a specific road situation, suchas on a mountain road, by using a representative value greater than theaverage according to the degree of expansion.

A state of charge limit range setting block 309 sets the limitingconditions regarding the state of charge for charge scheduling at thefollowing charge scheduling block 311. For the description of processingby this block 309, the characteristics of the battery 107 of the vehicleused in this embodiment will be described. FIG. 6 is a diagramillustrating the output characteristics of the battery in thisembodiment relative to the state of charge (hereinafter SOC). When theSOC is 100%, the maximum output is attained. When the SOC falls below60%, the output drops rapidly. As a result, the driving power of themotor weakens, and the driving capability deteriorates.

FIG. 7 illustrates the charge/discharge efficiency characteristics ofthe battery. The charge/discharge efficiency means the ratio of thelevel of discharge obtained to a given level of charge. Whereas a nearly100% charge/discharge efficiency is achieved in an SOC region of 95% orbelow, the efficiency drops beyond an SOC of 95%. At an SOC of 100%, anyfurther charge would be an overcharge, and charging is virtuallyimpossible, making the regenerative brake inoperable. Processing by thisblock 309 sets the limits of the target range of the SOC on the basis ofthe height distribution h(t) so as to prevent the driving ease fromdeteriorating at a prescribed significant level a at a point of time t.

First the lower limit to the target SOC is calculated. The height givesthe vehicle the electrical potential energy Eh(h) [J (joule)]represented by the following equation:

Eh(h)=Mgh  (3)

Pr (60≦soc(t)+KΔh≦100)>a  (4)

where M is the weight of the vehicle, and g the gravitationalacceleration. The electrical potential energy is recovered by theregenerative system as electrical energy when the height position haschanges. The variation in range of the SOC per meter of heightdifference then is a fixed value k [%/m], assuming the motor efficiencyis fixed. Therefore, the representative value of height ho(t) at apredicted point of time and the realized value hr(t) of height at a realpoint of time t being represented by Δh(t), the SOC will decrease orincrease by xΔh. The value of Δh(t) at a future point of time t is amatter of probability at the current time, and the distribution of Δh(t)values is determined uniquely by h(t). Therefore, by solving Equation(4) by using h(t), the range [e1(t), e2(t)] of the SOC(t) in which theSOC is kept between 65% and 100% can be calculated even if there is aprobability for k×Δh to vary relative to a prescribed significant levela (e.g. 0.99). This limit range [e1(t). e2(t)] regarding the setting ofthe SOC target at this point of time t is the output of the block 309.

The greater the dispersion of Δh, i.e. the greater the dispersion ofh(t), the narrower the range of [e1(t), e2(t)]. This allows setting anarrower SOC limit range in the charging schedule according to thedispersion of h(t). In this way, processing requires a fewer steps,although accuracy is decreased.

Next, the charge scheduling block 311 performs charge scheduling on thebasis of the representative value of height ho (t) at each point of timet calculated by the block 307 and the representative value of heightho(t) and the SOC limit, range [e1(t), e2(t)], and supplies acharge/discharge request to a driving power distribution unit 315 givingpriority to either power generation or driving (discharge) according tothe result of charge scheduling and the current SOC value. In the chargescheduling by this embodiment, the height position ho(t) of the vehicleat each point of time t (at five minutes' intervals from the currenttime until 30 minutes later) is assumed, and the target for the batterySOC to minimize the fuel consumption under this condition is calculatedfor each point of time. However, the target at each point of time shouldbe satisfy the condition of the limit range [e1(t), e2(t)]. If theactual SOC is greater than the SOC thereby calculated, the priority ofthe charge/discharge request is given to driving (discharge). If theactual SOC is smaller, the priority is given to generation.

A target axle output setting part 313 determines the target of drivingpower to be supplied to the driving axle on the basis of the acceleratorpedal treading angle APS, the brake pedal treading angle BRS and thevehicle speed V. First, according to the map shown in FIG. 8, thestandard value of the target axle output is determined from APS and thevehicle speed V. Further, the balance of the subtraction of the brakeamount according to the brake pedal treading angle at the ratio shown inFIG. 9 from this standard value is supplied as the target axle drivingoutput tTd.

The driving power distribution unit 315 calculates the engine output,motor output and generator output on the basis of a charge/dischargerequest from the block 311 and a target axle driving output from theblock 313, and supplies the respective target values to the engine,motor and generator. Here, the sum of the balance of the subtraction ofthe output required for power generation from the engine output and themotor output is the axle output. This axle output is caused to beidentical with tTd figured out by the block 313. The individual drivingratio of the engine, motor and generator are determined with referenceto tables prepared in advance. Two kinds of such tables are prepared,one giving priority to power generation by increasing the ratio of thegenerated power and the other giving priority to driving by increasingthe ratio of the motor driving power. Either is selectively read inaccordance with a charge/discharge request from the block 311.

FIG. 4 shows the flow of the processing by the vehicle control methodaccording to the embodiment of the invention shown in FIG. 3. At step401, the arrival range prediction part 301 predicts the arrival rangeS(t) of the vehicle. At step 403, the arrival probability calculationpart 303 calculates the arrival probability at each point included inthe vehicle's arrival probability range S(t).

At step 405, the height distribution calculation part 305 calculates theheight distribution h(t). At step 407, the representative height valuesetting part 307 calculates the representative height value ho(t) ateach point of time. At step 411, the charge scheduling part 311schedules the SOC.

At step 413, the target axle output setting part 313 sets the targetaxle output. At step 415, the driving power distribution unit 315 setsand supplies the driving target values of the engine, motor andgenerator.

Although the foregoing embodiment is a vehicle equipped with aregenerative system consisting of a battery and a motor, the presentinvention is not confined to this embodiment. A vehicle equipped with aregenerative system using elastic elements, compressed air, a flywheel,a hydraulic pump or the like also has its own output characteristics andefficiency characteristics like the output characteristics andefficiency characteristics of the battery illustrated in FIGS. 6 and 7.In a regenerative system using a flywheel, for instance, the kineticenergy of the vehicle is converted into the rotational energy of theflywheel and accumulated. Then, if the number of revolutions falls belowa certain level, it will become difficult to discharge energy. Or, ifthe number of revolutions rises beyond a certain upper limit, frictionalloss will become too great to allow the energy to be stored. Accordingto the characteristics of each regenerative system, the limit range ofregenerated energy accumulation is set like the limit range set by theblock 309 shown in FIG. 3.

The advantages of the invention manifested by this embodiments will nowbe described with reference to FIGS. 10A, 10B and 10C.

FIG. 10A illustrates a road environment in which a vehicle is about totravel. It is supposed that there is no particular traffic jam, and thatat a point of time 0 the vehicle is in a position marked with  and willtravel on the bold line in the direction of ◯ and Δ. FIG. 10B showsvariations in the SOC of the vehicle's battery where control isperformed without prediction of the future environment. As the vehicletravels uphill from the position of  to that of ◯ and thereby consumeselectric power, the SOC falls, and the motor output drops. Furtherduring the downhill run beyond the position marked with Δ, powergeneration by the regenerative brake raises the SOC beyond 100%, and theregenerative brake will no longer work. As opposed to this, variationsin the SOC of the battery under vehicle control according to theinvention are shown in FIG. 10C. Since the representative height valueof the mountain road from  to ◯ is known, the necessary SOC forclimbing is attained at the  point. Therefore, no drop in motor outputoccurs before the vehicle reaches the position marked with ◯. Further,during the trip from ◯ to Δ, charge scheduling is accomplished on thebasis of the representative value of height after further prescribing alimit to of the target SOC on the basis of a height distributionincluding both an uphill route and a downhill route at the positionmarked with Δ. As a result, satisfactory driving is ensured both whenthe vehicle travels downhill by the route marked with the bold line(variations in the SOC represented by the solid line in FIG. 10), theprobability of whose choice is high, and when an uphill route is chosen(variations in the SOC represented by the broken line in FIG. 10C).

A second preferred embodiment of the present invention will now bedescribed. FIG. 3 is a block diagram of processing by this embodiment,which differs from the first embodiment in that is provided with atarget route setting part 1101. The block 1101 calculates the optimalroute to the destination entered by the driver. The arrival probabilitycalculation part 303 in this embodiment, unlike its counterpart in thefirst embodiment, calculates the probability of reaching each link pointby using target route information entered from the block 1101. Thus, itassigns the highest probability (e.g. 90% or more) for the choice of aroute along the target route in the event the road branches, andincreases the probability for the choice of another route depending onthe road shape and the degree of congestion. (For instance, if thetarget route and another route are equal in width, the probability ofdeviation from the target route is 1%, and the probability increases toa maximum of 10% with an expansion in road width.) This method makespossible more efficient charge scheduling when a target route is given.Moreover, even if any deviation from the target route arises, there isno fear of the driving ease deteriorating substantially because thetarget SOC is limited to a certain level by the block 309.

A third preferred embodiment of the present invention will now bedescribed. FIG. 11 is a block diagram illustrating this embodiment.Blocks shown here bearing the same reference numerals as in FIG. 3function in respectively the same ways as their counterparts there. Inthe block diagram of FIG. 11, blocks 1205, 1207 and 1209 are providedrespectively in place of the blocks 305, 307 and 309 shown in FIG. 3. Avehicle speed distribution calculation part 1205 calculates the variablerange of the vehicle speed on the basis of traffic jam information ateach point of the reachable range, and calculates the distribution ofvehicle speed variable range at each point of time t, instead of theheight distribution, by synthesizing the speed variable range with theprobability of arrival. A representative vehicle speed setting part 1207calculates the representative value of the vehicle speed variable rangeat each point of time t. Then, a state of charge limit range settingpart 1209 sets the SOC limit range in charge scheduling by the followingblock 311 on the basis of the distribution of the vehicle speed variableranges. Here, the vehicle has, at a speed v, kinetic energy Ev(h) [J(joule) represented by the following equation.

Ev(v)=½Mv² (5)

Then, the variable range Δv of v becomes the varying factor ofregenerative energy in place of the height variable range Δh. In thesame way as Equation (4) was solved for the first embodiment, even wherethe vehicle speed varies by Δv, the target value range [e1(t), e2(t)]for keeping the SOC within a proper range at a significant level can becalculated. This is the output of the block 1209.

This embodiment is particularly effective where the vehicle is travelingat high speed on a road with no significant height differences. In sucha case, the determinant of regenerative energy is a variation in kineticenergy. On the basis of the distribution of this kinetic energy, chargescheduling is performed, and satisfactory driving ease can be therebysecured.

A fourth preferred embodiment of the present invention will now bedescribed. The block diagram of processing by this embodiment is similarto the block diagram shown in FIG. 3 except that blocks 303 and 1101 aredispensed with, and that the lock 305 calculates the height distributionon the basis of the assumption that the probability of arriving at anypoint within the reachable range is equal. This embodiment, thoughinferior in the accuracy of height distribution, has the advantage ofpermitting processing in a smaller number of steps. For this embodiment,the processing by the block 303 in the first, second and thirdembodiments can be replaced by processing to regard distances determinedby the average vehicle speed and the elapsed time from the currentgeographical point or points at a prescribed distance as the reachablerange. Though inferior in accuracy, processing is simpler.

A program for executing the hybrid vehicle control method according tothe invention can also be stored into a computer-readable recordingmedium and, when it is to be executed, loaded onto a memory forexecution.

According to the present invention, even where the destination of avehicle and a route to reach there are not indicated, driving of thevehicle can be scheduled on a long term basis by probability-basedprediction and fuel efficiency can be thereby enhanced. Furthermore,where a driving plan is made by specifying the route, even if deviationsfrom the planned route occur in actual driving, fuel efficiency anddriving conditions are controlled.

The preceding has been a description of the preferred embodiment of theinvention. It will be appreciated that deviations and modifications canbe made without departing from the scope of the invention, which isdefined by the appended claims.

What is claimed is:
 1. A method for controlling a hybrid vehicle whichincludes a regenerative system for converting kinetic energy and anengine, comprising the steps of: predicting a plurality of points thatthe hybrid vehicle can reach at a predetermined time, using stored mapinformation; calculating a probability that the hybrid vehicle reacheach one of the points; calculating a distribution of elevations thatthe hybrid vehicle can reach at the predetermined time; and controllingthe regenerative system and the engine based on the distribution ofelevations.
 2. The method for controlling a hybrid vehicle according toclaim 1 wherein said step of controlling calculates representative valueof elevations using the distribution of elevations and controls theregenerative system and the engine using the representative value ofelevations.
 3. The method for controlling a hybrid vehicle according toclaim 1 wherein said step of controlling calculates a distribution ofenergy states of the hybrid vehicle at the predetermined time using thedistribution of elevations and controls the regenerative system and theengine using the distribution of energy states.
 4. The method forcontrolling a hybrid vehicle according to claim 3 wherein said step ofcontrolling determines a setting range of target energy storage quantityaccording to the distribution of energy state at the predetermined timeand controls the regenerative system and the engine to satisfy thesetting range.
 5. The method for controlling a hybrid vehicle accordingto claim 1 wherein said step of calculating the probability calculatesthe probability by calculating a probability of route choice at ajunction including the map information, and the probability of routechoice uses the route chosen from routes connected to the junction. 6.The method for controlling a hybrid vehicle according to claim 5 whereinsaid step of calculating the probability changes the value of theprobability of route choice according to width of the routes.
 7. Themethod for controlling a hybrid vehicle according to claim 5, furthercomprising the step of receiving traffic congestion information thatshows a degree of traffic congestion of the routes and the step ofcalculating the probability changes the value of the probability ofroute choice according to the traffic congestion information.
 8. Acontroller of a hybrid vehicle for controlling a regenerative system forconverting kinetic energy and an engine included in the hybrid vehiclecomprising: means for predicting a plurality of points that the hybridvehicle can reach at predetermined time, using stored map information;means for calculating a probability that the hybrid vehicle reaches eachpoint of the points; means for calculating a distribution of elevationsthat the hybrid vehicle can reach at the predetermined time; and meansfor outputting a signal for controlling the regenerative system and theengine based on the distribution of elevations.
 9. The controller of ahybrid vehicle according to claim 8 wherein said means for outputtingcalculates representative value of elevations using the distribution ofelevations, and generates the signal for controlling the regenerativesystem and the engine using the representative values of elevations. 10.The controller of a hybrid vehicle according to claim 8 wherein saidmeans for outputting calculates distribution of energy state of thehybrid vehicle at the predetermined time using the distribution ofelevations, and generates the signal for controlling the regenerativesystem and the engine using the distribution of energy state.
 11. Thecontroller of a hybrid vehicle according to claim 10 wherein said meansfor outputting determines the setting range of target energy storagequantity according to the distribution of energy state at thepredetermined time and controls the regenerative system and the enginesatisfying the setting range.
 12. The controller of a hybrid vehicleaccording to claim 8 wherein said means for calculating the probabilitycalculates the probability by calculating probability of route choice ata junction using the map information, and the probability of routechoice shows degree of which route chosen from routes connected to thejunction.
 13. The controller of a hybrid vehicle according to claim 12wherein said means for calculating the probability changes a value ofthe probability of route choice according to width of the routes. 14.The controller of a hybrid vehicle according to claim 12, furthercomprising means for connecting a receiver within the hybrid vehicle toreceive traffic congestion information that shows a degree of trafficcongestion of the routes and wherein said means for calculating theprobability changes the value of the probability of route choiceaccording to the traffic congestion information.
 15. A hybrid vehicleincluding a regenerative system for converting kinetic energy and anengine comprising a vehicle controller responsive to stored mapinformation, and a processor for predicting a plurality of points thatthe hybrid vehicle can reach at a predetermined time, based on storedmap information which calculates a probability that the hybrid vehiclereach designated locations, the processor calculating a distribution ofelevations that the hybrid vehicle can reach at the predetermined timeusing the probability, and outputting a signal for controlling theregenerative system and the engine based on the distribution ofelevations; an engine controller connected to said vehicle controllerand said engine, and controlling said engine based on the signal; and aregenerative system controller connected to said vehicle controller andsaid regenerative system, and controlling said regenerative system basedon the signal.
 16. The hybrid vehicle according to claim 15, furthercomprising a map database.
 17. The hybrid vehicle according to claim 15wherein said processor calculates representative values of elevationsusing the distribution of elevations, and generates the signal forcontrolling the regenerative system and the engine using therepresentative value of elevations.
 18. The hybrid vehicle according toclaim 15 wherein said processor calculates distribution of energy stateof the hybrid vehicle at the predetermined time using the distributionof elevations, and generates the signal for controlling the regenerativesystem and the engine using the distribution of energy state.
 19. Thehybrid vehicle according to claim 18 wherein said processor determinesrange of target energy storage quantity according to the distribution ofenergy state at the predetermined time and controls the regenerativesystem and the engine to satisfy the range.
 20. The hybrid vehicleaccording to claim 15 wherein said processor calculates the probabilityby calculating probability of route choice at a junction included themap information, and the probability of route choice shows a degree ofwhich route is chosen from routes connected to the junction.
 21. Thehybrid vehicle according to claim 20 wherein said processor changes avalue of the probability of route choice according to width of theroutes.
 22. The hybrid vehicle according to claim 20, further comprisinga receiver connected to said vehicle controller which receives trafficcongestion information that shows degree of traffic congestion of theroutes, wherein said processor changes value of probability of routechoice according to the traffic congestion information.
 23. A controllerfor a hybrid vehicle for controlling a regenerative system forconverting kinetic energy and an engine included the hybrid vehiclecomprising: means for predicting a plurality of points that the hybridvehicle can reach at predetermined time, using stored map information;means for calculating the hybrid vehicle's velocity variable range atthe predetermined time; means for calculating distribution of thevelocity variable range at the predetermined time, using the probabilityand the velocity variable range; and means for outputting a signal forcontrolling the regenerative system and the engine based on thedistribution of the velocity variable range.